Prostate Imaging Research Articles

IPEM topical report: the first UK survey of cone beam CT dose indices in radiotherapy verification imaging for adult patients

Cone beam CT is integral to most modern radiotherapy treatments. The application of daily and repeat CBCT imaging can lead to high imaging doses over a large volume of tissue that extends beyond the treatment site. Hence, it is important to ensure exposures are optimised to keep doses as low as reasonably achievable, whilst ensuring images are suitable for the clinical task. This IPEM topical report presents the results of the first UK survey of dose indices in radiotherapy CBCT. Dose measurements, as defined by the cone beam dose index (CBDIw), were collected along with protocol information for seven treatment sites. Where a range of optimised protocols were available in a centre, a sample of patient data demonstrating the variation in protocol use were requested. Protocol CBDIwvalues were determined from the average dosimetry data for each type of linear accelerator, and median CBDIwand scan length were calculated for each treatment site at each centre. Median CBDIwvalues were compared and summary statistics derived that enable the setting of national dose reference levels (DRLs). A total of 63 UK radiotherapy centres contributed data. The proposed CBDIwDRLs are; prostate 20.6 mGy, gynaecological 20.8 mGy, breast 5.0 mGy, 3D-lung 6.0 mGy, 4D-lung 11.8 mGy, brain 3.5 mGy and head/neck 4.2 mGy. However, large differences between models of imaging system were noted. Where centres had pro-active optimisation strategies in place, such as sized based protocols with selection criteria, dose reductions on the 'average' patient were possible compared with vendor defaults. Optimisation of scan length was noted in some clinical sites, with Elekta users tending to fit different collimators for prostate imaging (relatively short) compared with gynaecological treatments (longest). This contrasts with most Varian users who apply the default scan length in most cases.

Detecting Clinically Significant Prostate Cancer in PI-RADS 3 Lesions Using T2w-Derived Radiomics Feature Maps in 3T Prostate MRI

Prostate Imaging Reporting and Data System version 2.1 (PI-RADS) category 3 lesions are a challenge in the clinical workflow. A better detection of the infrequently occurring clinically significant prostate cancer (csPCa) in PI-RADS 3 lesions is an important objective. The purpose of this study was to evaluate if feature maps calculated from T2-weighted (T2w) 3 Tesla (3T) MRI can help detect csPCa in PI-RADS category 3 lesions. In-house biparametric 3T prostate MRI examinations acquired between January 2019 and June 2023 because of elevated prostate-specific antigen (PSA) levels were retrospectively screened. Inclusion criteria were a PI-RADS 3 lesion and available results of an ultrasound-guided targeted and systematic biopsy. Exclusion criteria were a simultaneous PI-RADS category 4 or 5 lesion and hip replacement. Target lesions with the International Society of Urological Pathology (ISUP) grade group 1 were rated clinically insignificant PCa (ciPCa) and ≥2 csPCa. This resulted in 52 patients being included in the final analysis, of whom 11 (21.1%), 8 (15.4%), and 33 (63.5%) patients had csPCa, ciPCa, and no PCa, respectively, with the latter two groups being combined as non-csPCa. Eight of the csPCas were located in the peripheral zone (PZ) and three in the transition zone (TZ). In the non-csPCa group, 29 were located in the PZ and 12 in the TZ. Target lesions were marked with volumes of interest (VOIs) on axial T2w images. Axial T2w images were then converted to 93 feature maps. VOIs were copied into the maps, and feature quantity was retrieved directly. Features were tested for significant differences with the Mann–Whitney U-test. Univariate models for single feature performance and bivariate models implementing PSA density (PSAD) were calculated. Ten map-derived features differed significantly between the csPCa and non-csPCa groups (AUCs: 0.70–0.84). The diagnostic performance for TZ lesions (AUC: 0.83–1.00) was superior to PZ lesions (AUC: 0.74–0.85). In the bivariate models, performance in the PZ improved with AUCs >0.90 throughout. Parametric feature maps alone and as bivariate models with PSAD can (?) noninvasively identify csPCa in PI-RADS 3 lesions and could serve as a quantitative tool reducing ambiguity in PI-RADS 3 lesions.

Improving Prostate Image Segmentation Based on Equilibrium Optimizer and Cross-Entropy

Over the past decade, the development of computer-aided detection tools for medical image analysis has seen significant advancements. However, tasks such as the automatic differentiation of tissues or regions in medical images remain challenging. Magnetic resonance imaging (MRI) has proven valuable for early diagnosis, particularly in conditions like prostate cancer, yet it often struggles to produce high-resolution images with clearly defined boundaries. In this article, we propose a novel segmentation approach based on minimum cross-entropy thresholding using the equilibrium optimizer (MCE-EO) to enhance the visual differentiation of tissues in prostate MRI scans. To validate our method, we conducted two experiments. The first evaluated the overall performance of MCE-EO using standard grayscale benchmark images, while the second focused on a set of transaxial-cut prostate MRI scans. MCE-EO’s performance was compared against six stochastic optimization techniques. Statistical analysis of the results demonstrates that MCE-EO offers superior performance for prostate MRI segmentation, providing a more effective tool for distinguishing between various tissue types.

A sustainable and expedited ‘One‐Stop’ prostate cancer diagnostic pathway to reduce environmental impact and enhance accessibility

AbstractObjectiveTo assess the carbon footprint, accessibility, and diagnostic performance of an expedited ‘One‐Stop’ prostate cancer (PCa) diagnostic pathway.Materials and methodsA total of 1083 consecutive patients undergoing magnetic resonance imaging (MRI) followed by transrectal ultrasound fusion‐guided prostate biopsy (PBx) were identified from a prospective database. The patients were divided according to the diagnostic pathway: One‐Stop, with MRI and same‐day PBx (3 hours apart), or Standard, with MRI followed by a second visit for PBx. Socioeconomic status was evaluated by the Distressed Communities Index (DCI) and the carbon footprint by the United States (U.S.) Environmental Protection Agency Greenhouse Gases Equivalencies Calculator.ResultsOverall, 260 patients underwent the One‐Stop and 823 the Standard pathway. The One‐Stop patients lived farther from the hospital (163 vs. 23 km; p < 0.001), had lower socioeconomic status with DCI scores of 49 versus 30 (p < 0.001), and were more likely to be Latinos (21% vs. 13%, p < 0.001) compared to the Standard patients, respectively. The One‐Stop saved 69 575 km in round trips, over 16 tons of travel‐related CO2 emissions, and $8214 U.S. dollars. For patients with Prostate Imaging Reporting & Data System (PIRADS) 3–5, the clinically significant PCa detection (53% vs. 50%, p = 0.55) was similar for the One‐Stop and Standard pathways, respectively.ConclusionsThe One‐Stop PCa diagnostic pathway reduces carbon footprint, distance travelled, and patient‐level cost while maintaining clinical outcomes comparable to the Standard pathway. It facilitates access to tertiary‐level care for minorities and underserved populations.

Comparison in prostate cancer diagnosis with PSA 4–10 ng/mL: radiomics-based model VS. PI-RADS v2.1

BackgroundTo evaluate accuracy of MRI-based radiomics in diagnosing prostate cancer (PCa) in patients with PSA levels between 4 and 10 ng/mL and compare it with the latest Prostate Imaging Reporting and Data System (PI-RADS v2.1) score.Methods221 patients with prostate lesions and PSA levels in 4–10 ng/mL, including 154 and 67 cases in the training and validation groups. Pathological confirmation of all patients was accomplished by the use of MRI-TRUS fusion targeted biopsy or systematic transrectal ultrasound (TRUS) guided biopsy. 851 radiomic features were extracted from each lesion of ADC and T2WI images. The least absolute shrinkage and selection operator (LASSO) regression algorithm and logistic regression were employed to select features and build the ADC and T2WI model. The combined model was obtained based on the ADC and T2WI features. The clinical benefit and diagnostic accuracy of the three radiomics models and PI-RADS v2.1 score were evaluated.Results10 radiomic features were ultimately selected from the ADC images, 13 from the T2WI images and 7 from the combined models. The ADC, T2WI and combined models achieved satisfactory diagnostic accuracy in the training [AUC:0.945 (ADC), 0.939 (T2WI), 0.979 (combined)] and validation groups [AUC: 0.942 (ADC), 0.943 (T2WI), 0.959 (combined)], which was significantly higher than those in PI-RADS v2.1 model (0.825 for training cohort and 0.853 for validation cohort). Compared with the PI-RADS v2.1 score, the three radiomics models generated superior PCa diagnostic performance in both the training (p = 0.002, p = 0.005, p < 0.001) and validation groups (p = 0.045, p = 0.035, p = 0.015).ConclusionRadiomics based on ADC and T2WI images can better identify PCa in patients with PSA 4–10 ng/mL, and MRI-based radiomics significantly outperforms the PI-RADS v2.1 score.Clinical trial numberNot applicable.

Predictive ability of magnetic resonance imaging (MRI) for detecting prostate cancer and its clinical significance in MRI-targeted biopsy for prostate imaging reporting and data system (PI-RADS) ≥3 lesions

Predictive ability of magnetic resonance imaging (MRI) for detecting prostate cancer and its clinical significance in MRI-targeted biopsy for prostate imaging reporting and data system (PI-RADS) ≥3 lesions

ProstateZones – Segmentations of the prostatic zones and urethra for the PROSTATEx dataset

Manual segmentations are considered the gold standard for ground truth in machine learning applications. Such tasks are tedious and time-consuming, albeit necessary to train reliable models. In this work, we present a dataset with expert segmentations of the prostatic zones and urethra for 200 randomly selected patients from the PROSTATEx dataset. Notably, independent duplicate segmentations were performed for 40 patients, providing inter-reader variability data. This results in a total of 240 segmentations. This dataset can be used to train machine learning models or serve as an external test set for evaluating models trained on private data, thereby addressing a current gap in the field. The delineated structures and terminology adhere to the latest Prostate Imaging Reporting and Data Systems v2.1 guidelines, ensuring consistency.

Comparison between 18F-DCFPyL PET/MRI-guided ultrasound fusion targeted biopsy and systematic biopsy for tumor detection and grading in selected patients: A prospective randomized controlled trial

ObjectiveTo compare the upgrade rate and cancer detection rate between 18F-DCFPyL PET/MRI-guided ultrasound fusion targeted biopsy and systematic biopsy in selected patients with suspected prostate cancer (the multiparametric MRI prostate imaging reporting and data system score ≥4 and molecular imaging prostate-specific membrane antigen score of prostate-specific membrane antigen PET image ≥2). MethodsEighty-seven selected biopsy-naive patients were randomized into two groups: targeted biopsy (n=41) and systematic biopsy (control; n=46). Those with negative initial results underwent a repeat biopsy using the alternative method. Patients diagnosed with clinically significant prostate cancer proceed to radical prostatectomy. The primary outcome was the upgrade rate. Additional outcomes, including the cancer detection rate, incidence of repeat biopsy, positive surgical margin, complications, and prostate-specific antigen level at 6 weeks postoperatively, were compared between the groups using Pearson or Fisher's exact tests, as appropriate. ResultsIn the study, prostate cancer was ultimately detected in all patients. The targeted biopsy group successfully identified all tumors, whereas five patients in the control group initially missed their tumors. The pathological upgrade rates for the targeted biopsy and control groups were 31.7 % and 56.5 %, respectively. Overall, the detection rate for clinically significant prostate cancer (the International Society of Urological Pathology grade ≥2) was significantly higher in the targeted biopsy group (92.7 %) compared with the control group (76.1 %, p=0.035). However, no significant difference was found in the detection rate of all prostate cancer. Complications (Clavien–Dindo grade ≤2) occurred in both the targeted biopsy group (n=11) and the control group (n=13). No statistically significant difference was observed between the groups in terms of positive surgical margin, complications, and 6-week postoperative prostate-specific antigen level. The main limitation is the small population. Conclusion18F-DCFPyL PET/MRI-guided ultrasound fusion targeted biopsy alone was an efficient modality in diagnosing selected patients with prostate cancer.

Evaluating Biparametric Versus Multiparametric Magnetic Resonance Imaging for Diagnosing Clinically Significant Prostate Cancer: An International, Paired, Noninferiority, Confirmatory Observer Study

Background and objectiveBiparametric magnetic resonance imaging (bpMRI), excluding dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), is a potential replacement for multiparametric MRI (mpMRI) in diagnosing clinically significant prostate cancer (csPCa). An extensive international multireader multicase observer study was conducted to assess the noninferiority of bpMRI to mpMRI in csPCa diagnosis. MethodsAn observer study was conducted with 400 mpMRI examinations from four European centers, excluding examinations with prior prostate treatment or csPCa (Gleason grade [GG] ≥2) findings. Readers assessed bpMRI and mpMRI sequentially, assigning lesion-specific Prostate Imaging Reporting and Data System (PI-RADS) scores (3–5) and a patient-level suspicion score (0–100). The noninferiority of patient-level bpMRI versus mpMRI csPCa diagnosis was evaluated using the area under the receiver operating curve (AUROC) alongside the sensitivity and specificity at PI-RADS ≥3 with a 5% margin. The secondary outcomes included insignificant prostate cancer (GG1) diagnosis, diagnostic evaluations at alternative risk thresholds, decision curve analyses (DCAs), and subgroup analyses considering reader expertise. Histopathology and ≥3 yr of follow-up were used for the reference standard. Key findings and limitationsSixty-two readers (45 centers and 20 countries) participated. The prevalence of csPCa was 33% (133/400); bpMRI and mpMRI showed similar AUROC values of 0.853 (95% confidence interval [CI], 0.819–0.887) and 0.859 (95% CI, 0.826–0.893), respectively, with a noninferior difference of –0.6% (95% CI, –1.2% to 0.1%, p < 0.001). At PI-RADS ≥3, bpMRI and mpMRI had sensitivities of 88.6% (95% CI, 84.8–92.3%) and 89.4% (95% CI, 85.8–93.1%), respectively, with a noninferior difference of –0.9% (95% CI, –1.7% to 0.0%, p < 0.001), and specificities of 58.6% (95% CI, 52.3–63.1%) and 57.7% (95% CI, 52.3–63.1%), respectively, with a noninferior difference of 0.9% (95% CI, 0.0–1.8%, p < 0.001). At alternative risk thresholds, mpMRI increased sensitivity at the expense of reduced specificity. DCA demonstrated the highest net benefit for an mpMRI pathway in cancer-averse scenarios, whereas a bpMRI pathway showed greater benefit for biopsy-averse scenarios. A subgroup analysis indicated limited additional benefit of DCE MRI for nonexperts. Limitations included that biopsies were conducted based on mpMRI imaging, and reading was performed in a sequential order. Conclusions and clinical implicationsIt has been found that bpMRI is noninferior to mpMRI in csPCa diagnosis at AUROC, along with the sensitivity and specificity at PI-RADS ≥3, showing its value in individuals without prior csPCa findings and prostate treatment. Additional randomized prospective studies are required to investigate the generalizability of outcomes.

The “Hungry Judge” effect on prostate MRI reporting: Chronobiological trends from 35’004 radiologist interpretations

AimTo investigate the associations between the hour of the day and Prostate Imaging–Reporting and Data System (PI-RADS) scores assigned by radiologists in prostate MRI reports. Materials and methodsRetrospective single-center collection of prostate MRI reports over an 8-year period. Mean PI-RADS scores assigned between 0800 and 1800 h were examined with a regression model. ResultsA total of 35′004 prostate MRI interpretations by 26 radiologists were included. A significant association between the hour of day and mean PI-RADS score was identified (β2 = 0.005, p < 0.001), with malignant scores more frequently assigned later in the day. ConclusionThese findings suggest chronobiological factors may contribute to variability in radiological assessments. Though the magnitude of the effect is small, this may potentially add variability and impact diagnostic accuracy.

Inter-reader reliability and diagnostic accuracy of PI-RADS scoring between academic and community care networks: How wide is the gap?

ImportanceThe Prostate Imaging Reporting & Data System (PI-RADS) scoring guidelines were developed to address the substantial variation in interpretation and reporting of prostate cancer (PCa) multiparametric MRI (mpMRI) results, and subsequent updates have sought to further improve inter-reader reliability. Nonetheless, the variability of PI-RADS scoring in real-world settings may represent a continuing challenge to the widespread standardization of prostate mpMRI and limit its overall clinical benefit. ObjectiveTo assess variability in mpMRI interpretation and reporting of PCa, we evaluated the discrepancies in PI-RADS scoring between community practices and a tertiary academic care center. Design, setting, and participantsWe identified 262 mpMRI studies from nonacademic facilities, reinterpreted by radiologists at our institution between January 2016 and July 2022. Results of targeted MRI fusion biopsy were identified for 193 of these patients, totaling 302 lesions. PI-RADS scoring from both community and academic interpreters were recorded in addition to presence of clinically significant PCa (csPCa) on pathological analysis of targeted cores. Main Outcome and measuresThe primary outcome was inter-reader reliability via intraclass correlation (ICC) and the kappa statistic. We also assessed the diagnostic accuracy of PI-RADS scoring for detecting csPCa for both cohorts via receiver operator characteristics (ROC) analysis and compared these findings using paired-sample area difference under curve analysis. ResultsInter-reader agreement and reliability of PI-RADS scoring per lesion was generally poor (absolute agreement ICC = 0.393, 95% CI: 0.288–0.488; consistency ICC = 0.407, 95% CI: 0.308–0.497; kappa = 0.336, 95% CI: 0.267–0.406). Reliability results from studies obtained after the publication of PI-RADSv2.1 were similar to those of the overall analysis. No agreement was observed in the subgroup of lesions scored as PIRADS 3 by community interpreters. No statistically significant difference in diagnostic accuracy was observed between cohorts (ROC area under curve [AUC]: 0.759 vs. 0.785, respectively; P = 0.337). PI-RADS 3 was determined to be the optimal cutoff for detecting clinically significant disease in both cohorts. Conclusions and relevanceOur results suggest that mpMRI diagnostic accuracy for detecting csPCa is not significantly different between academic and community practices. However, significantly poor reliability of mpMRI was observed between cohorts, suggesting the risk of introducing practice variation for community prostate cancer management. Variability, particularly for PI-RADS 3 lesions, can lead to inconsistent biopsy recommendations, which may result in missed csPCa or unnecessary biopsies.

AI-derived Tumor Volume from Multiparametric MRI and Outcomes in Localized Prostate Cancer.

Background An artificial intelligence (AI)-based method for measuring intraprostatic tumor volume based on data from MRI may provide prognostic information. Purpose To evaluate whether the total volume of intraprostatic tumor from AI-generated segmentations (VAI) provides independent prognostic information in patients with localized prostate cancer treated with radiation therapy (RT) or radical prostatectomy (RP). Materials and Methods For this retrospective, single-center study (January 2021 to August 2023), patients with cT1-3N0M0 prostate cancer who underwent MRI and were treated with RT or RP were identified. Patients who underwent RT were randomly divided into cross-validation and test RT groups. An AI segmentation algorithm was trained to delineate Prostate Imaging Reporting and Data System (PI-RADS) 3-5 lesions in the cross-validation RT group before providing segmentations for the test RT and RP groups. Cox regression models were used to evaluate the association between VAI and time to metastasis and adjusted for clinical and radiologic factors for combined RT (ie, cross-validation RT and test RT) and RP groups. Areas under the receiver operating characteristic curve (AUCs) were calculated for VAI and National Comprehensive Cancer Network (NCCN) risk categorization for prediction of 5-year metastasis (RP group) and 7-year metastasis (combined RT group). Results Overall, 732 patients were included (combined RT group, 438 patients; RP group, 294 patients). Median ages were 68 years (IQR, 62-73 years) and 61 years (IQR, 56-66 years) for the combined RT group and the RP group, respectively. VAI was associated with metastasis in the combined RT group (median follow-up, 6.9 years; adjusted hazard ratio [AHR], 1.09 per milliliter increase; 95% CI: 1.04, 1.15; P = .001) and the RP group (median follow-up, 5.5 years; AHR, 1.22; 95% CI: 1.08, 1.39; P = .001). AUCs for 7-year metastasis for the combined RT group for VAI and NCCN risk category were 0.84 (95% CI: 0.74, 0.94) and 0.74 (95% CI: 0.80, 0.98), respectively (P = .02). Five-year AUCs for the RP group for VAI and NCCN risk category were 0.89 (95% CI: 0.80, 0.98) and 0.79 (95% CI: 0.64, 0.94), respectively (P = .25). Conclusion The volume of AI-segmented lesions was an independent, prognostic factor for localized prostate cancer. © RSNA, 2024 Supplemental material is available for this article.

Effect of Precise Dissection and Reconstruction of the Prostate Apex and Bladder Neck in Radical Prostatectomy on Urinary Control Improvement

To investigate the impact of the precise dissection and reconstruction of the prostate apex and bladder neck urethra during radical prostatectomy on the improvement in postoperative urinary control in patients with prostate cancer. A retrospective study was conducted. A total of 131 prostate cancer patients who underwent robot-assisted radical prostatectomy at our institution between January 1, 2023 and December 31, 2023 were enrolled. The subjects were divided into two groups, with 64 in the experimental group and 67 in the control group. Patients in the experimental group underwent radical prostatectomy in a modified approach, while those in the control group underwent conventional radical prostatectomy. Propensity score matching was employed to match the two groups at a 1-to-1 ratio based on age, body mass index (BMI), preoperative prostate specific antigen (PSA), prostate volume, Prostate Imaging Reporting and Data System (PI-RADS) scores, biopsy Gleason score, and preoperative urinary control status. After matching, we compared the preoperative baseline data, surgical margin positivity rates, and urinary control status at 3 months post operation between the two groups. Urinary control was assessed before and after surgery using the International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form (ICIQ-UI SF) scale. A total of 56 pairs of patients were successfully matched between the experimental group and the control group through 1-to-1 propensity score matching. At 3 months after surgery, the median score for ICIQ-SF scale of the experimental group was 7.0 points, while that of the control group was 9.5 points, with the difference being statistical significant (P<0.05). There was no significant difference in the positive rate of incision margins between the experimental group and the control group. Multiple linear regression analysis showed that both the prostate volume and the Gleason score in the experimental group were positively correlated with the ICIQ-UI SF scores 3 months after surgery (P<0.05), while the age of patients in the control group was positively correlated with ICIQ-UI SF score 3 months after surgery (P<0.05). Precise dissection and reconstruction of the prostate apex and bladder neck urethra during radical prostatectomy significantly improve the postoperative urinary control of patients at 3 months after surgery.

Role of contrast agent in evaluation of periprostatic invasion in prostate cancer.

Our study aims to demonstrate the detection of invasion by biparametric prostate MRI (bpMRI). The cases whose histopathological diagnosis was prostate cancer (PCa) and whose mpMRI report was reported as PIRADS 4 and 5 were evaluated retrospectively by two radiologists with different prostate imaging experiences. The images were grouped into two data sets. Dataset-1 was bpMRI, and dataset-2 was mpMRI. Two radiologists first evaluated dataset-1 independently of each other, and 1 month later, dataset-2. They recorded whether there was an invasion and where it was seen in the patients. Then, the results were compared. A total of 75 patients were included in the study. Periprostatic invasion was detected in 33 of the patients. Both the 1st reader and the 2nd reader image detected all the cases with invasion (100%) separately between dataset-1 and set-2. Compatibility for image dataset-1 and dataset-2 between both readers was observed to be excellent. There is no need to use contrast agent to evaluate periprostatic invasion and to have an idea about local staging in PCa patients.

Evaluating Prostate Cancer: The Diagnostic Impact of MRI and Its Relationship With Transrectal Ultrasound (TRUS)-Guided Biopsy.

Background Prostate disorders, including benign enlargement and malignancy, are commonly evaluated through imaging techniques. Historically, transrectal ultrasound (TRUS) has been used for prostate imaging and biopsy. However, multiparametric MRI (mpMRI), which integrates structural and functional imaging methods, offers enhanced diagnostic capabilities. This study evaluates the effectiveness of mpMRI, including its grading via Prostate Imaging - Reporting and Data System (PI-RADS) or Likert scoring, in distinguishing between benign and malignant prostatic conditionsand compares these findings with TRUS outcomes. Methodology This prospective study enrolled 30 male patients aged 45 to 75 years (mean age 60 years), selected based on prostatic abnormalities, elevated prostate-specific antigen (PSA) levels (>4 ng/dL), or palpable nodules detected via digital rectal examination. MRI, including PI-RADS or Likert scoring, was utilized to assess prostatic lesions, and results were compared with histopathological data obtained from TRUS-guided biopsies. Results Among the 30 patients, common symptoms included urinary retention (60%) and painful urination (53.3%). Malignant tumors were diagnosed in 12 patients (40%). MRI identified eight cases with enlarged transitional zones and irregular signals in peripheral zones (benign prostatic hyperplasia with tumor)and four cases with irregular signals in both zones (sarcoma). Concordance between MRI T2-weighted (T2W) observations and biopsy results showed 60% malignancy detection. Sensitivity assessments revealed MRI detected 15 true-positives (50%), TRUS detected six true positives (20%), and multivoxel spectroscopic analysis (MVS) identified 14 true-positives (46.7%). PI-RADS or Likert scoring of mpMRI was correlated with TRUS outcomes, highlighting its enhanced diagnostic accuracy compared to TRUS alone. Conclusion While TRUS remains a standard diagnostic tool, it is limited by significant sampling errors and complications. The integration of mpMRI, with its grading system, significantly improves diagnostic accuracy and treatment planning. Although mpMRI alone has limitations, its combination with contrast-enhanced MRI, diffusion-weighted imaging, and MR spectroscopy offers a comprehensive approach to enhanced prostate cancer detection.

Diagnostic utility of prostate health index density prior to MRI-ultrasound fusion targeted biopsy.

Prostate biopsy can be prone to complications and thus should be avoided when unnecessary. Although the combination of magnetic resonance imaging (MRI), the prostate health index (PHI), and PHI density (PHID) has been shown to improve detection of clinically significant prostate cancer (csPCa), there is limited information available assessing its clinical utility. We sought to determine whether using PHID could enhance the detection of PCa on MRI ultrasound fusion-targeted biopsy (MRF-TB) compared to other biomarker cutoffs. Between June 2015 and December 2020, 302 men obtained PHI testing before MRF-TB at a single institution. We used descriptive statistics, multivariable logistic regression, and receiver operating characteristic curves to determine the predictive accuracy of PHID and PHI to detect ≥ Gleason grade group (GGG) 2 PCa and identify cutoff values. Any cancer grade was identified in 75.5% of patients and ≥ GGG2 PCa was identified in 45% of patients. The median PHID was 1.05 [interquartile range (IQR) 0.59-1.64]. A PHID cutoff of 0.91 had a higher discriminatory ability to predict ≥ GGG2 PCa compared to PHI > 27, PHI > 36, and prostate specific-antigen (PSA) density > 0.15 (AUC: 0.707 vs. 0.549 vs. 0.620 vs. 0.601), particularly in men with Prostate Imaging Reporting and Data System (PI-RADS) 1-2 lesions on MRI (AUC: 0.817 vs. 0.563 vs. 0.621 vs. 0.678). At this cutoff, 35.0% of all the original biopsies could be safely avoided (PHID < 0.91 and no ≥ GGG2 PCa) and csPCa would be missed in 9.67% of patients who would have been biopsied. In patients with PI-RADS 1-2 lesions using a PHID cutoff of 0.91, 56.8% of biopsies could be safely avoided while missing 0 csPCa. These findings suggest that a PHID cutoff of 0.91 improves the selection of patients with elevated prostate-specific antigen who are referred for prostate biopsy, and potentially in patients with PI-RADS 1-2 lesions.

Explainable artificial intelligence-driven prostate cancer screening using exosomal multi-marker based dual-gate FET biosensor

Prostate Imaging Reporting and Data System (PI-RADS) score, a reporting system of prostate MRI cases, has become a standard prostate cancer (PCa) screening method due to exceptional diagnosis performance. However, PI-RADS 3 lesions are an unmet medical need because PI-RADS provides diagnosis accuracy of only 30–40% at most, accompanied by a high false-positive rate. Here, we propose an explainable artificial intelligence (XAI) based PCa screening system integrating a highly sensitive dual-gate field-effect transistor (DGFET) based multi-marker biosensor for ambiguous lesions identification. This system produces interpretable results by analyzing sensing patterns of three urinary exosomal biomarkers, providing a possibility of an evidence-based prediction from clinicians. In our results, XAI-based PCa screening system showed a high accuracy with an AUC of 0.93 using 102 blinded samples with the non-invasive method. Remarkably, the PCa diagnosis accuracy of patients with PI-RADS 3 was more than twice that of conventional PI-RADS scoring. Our system also provided a reasonable explanation of its decision that TMEM256 biomarker is the leading factor for screening those with PI-RADS 3. Our study implies that XAI can facilitate informed decisions, guided by insights into the significance of visualized multi-biomarkers and clinical factors. The XAI-based sensor system can assist healthcare professionals in providing practical and evidence-based PCa diagnoses.

A Multi-Institutional Study of Magnetic Resonance/Ultrasound Fusion-Guided Nanoparticle-Directed Focal Therapy for Prostate Ablation.

Focal therapy aims to provide a durable oncologic treatment option for men with prostate cancer (PCa), while preserving their quality of life. Most focal therapy modalities rely on the direct tissue effect, resulting in a possible nontargeted approach to ablation. Here, we report the results of the first human feasibility trial utilizing nanoparticle-directed focal photothermal ablation for PCa. A prospective, open-label, single-arm, multicenter study of men with localized PCa in Gleason Grade Group 1 to 3 was conducted. Men received a single infusion of gold nanoparticles (AuroShells), followed by magnetic resonance (MR)/ultrasound (US) fusion-guided laser excitation of the target tissue to induce photothermal ablation. MRI was used to assess the effectiveness of prostate tissue ablation at 48 to 96 hours, 3 months, and 12 months post treatment. At 3 months, a targeted fusion biopsy of the lesion(s) was conducted. At 12 months, a targeted fusion biopsy and standard templated biopsy were performed. Treatment success was determined based on a negative MR/US fusion biopsy outcome within the treated area. Forty-six men were enrolled in the study, and 44 men with 45 lesions completed nanoparticle infusion and laser treatment. The mean PSA level at baseline was 9.5 ng/mL, which decreased to 5.9 ng/mL at 3 months and to 4.7 ng/mL at 12 months (P < .0001). The oncologic success rates at 3 and 12 months resulted in 29 (66%) and 32 (73%) of 44 patients, respectively, being successfully treated, confirmed with negative MR/US fusion biopsies within the ablation zone. Among Gleason Grade Group, maximum lesion diameter on MRI, prostate volume, and Prostate Imaging Reporting and Data System scoring, the maximum lesion diameter was significantly associated with the odds of treatment failure at 12 months (P = .046). Nanoparticle-directed focal laser ablation of neoplastic prostate tissue resulted in 73% of patients with successful treatment at 12 months post treatment, confirmed by negative MR/US fusion biopsy of the treated lesion and a systematic biopsy. 02680535.

Incorporation of mpMRI before prostate biopsy shall be universal or selective: A prospective observational study

Purpose: The aim of this study is to evaluate the role of multiparametric magnetic resonance imaging (mpMRI) as a triage workup in the diagnostic pathway of suspected prostate cancer (PCa) in our population. Material and methods: This prospective observational study was conducted at lesser than details of site are removed for blinded peer review &gt; on biopsy-naive patients from May 2021 to December 2022. We included patients aged 40 to 80 years with clinical suspicion of PCa, prostate-specific antigen (PSA) level &gt;4 ng/mL, abnormal digital rectal examination (DRE), or all the above. All patients first underwent 1.5-T mpMRI and transrectal ultrasound-guided biopsy using the cognitive biopsy technique. Results: A total of 95 patients were included, with the majority of them (64.21%) being ≥66 years old. Of these, 69 patients had abnormal DRE findings, 89 had PSA ≥4 ng/mL, and 64 had both elevated PSA and abnormal DRE findings. PCa was detected in 6.25%, 54.84%, 71.43%, and 96.43% of patients with lesions of Prostate Image Reporting and Data System scores of 2, 3, 4, and 5, respectively. Using Prostate Image Reporting and Data System score of 3 as a biopsy threshold resulted in high sensitivity (98.31%) and low specificity (41.67%) for PCa detection. The proportion of Gleason score of ≥7 cancer-detected cores in the magnetic resonance imaging-guided cognitive biopsy was significantly higher than that in the standard 12-core biopsy (86.54% versus 61.45%; P &lt; 0.001). Conclusion: The incorporation of prebiopsy mpMRI could be used as a diagnostic pathway for suspected PCa before transrectal ultrasound-guided biopsy.

Natural history of PIRADS-2 lesions on serial multiparametric magnetic resonance imaging: Real-life data from an Academic Center

Introduction/BackgroundThe natural history of prostate imaging reporting and data system (PIRADS) score 2 lesions on serial mpMRIs is largely unknown. Herein, we aimed to evaluate the patients with PIRADS-2 index lesions by using serial mpMRI scans to reveal the rates of mpMRI upgrade in PIRADS score and prostate cancer (PCa) detection. Methods/MaterialsAll mpMRI scans with a PIRADS-2 index lesion from our mpMRI database were evaluated retrospectively. Data from 214 biopsy-naïve patients with a PIRADS-2 index lesion on the initial mpMRI who then underwent at least 1 follow-up mpMRI were reevaluated by an experienced uroradiologist and only those (n = 172) who had a PIRADS-2 index lesion on the initial mpMRI according to PIRADS v2.1 were included in the study. mpMRI progression was defined as the detection of any PIRADS ≥3 lesion at follow-up mpMRI. Histopathological results were evaluated in patients undergoing biopsy upon mpMRI progression. ResultsA total of 172 patients with a mean age of 60.1 ± 8.6 years were evaluated. The median PSA at baseline mpMRI was 4.7 (IQR; 3.3–6.7) ng/dl. Overall mpMRI progression was detected in 54 patients (31.4%), 37 were upgraded to PIRADS-3, 16 to PIRADS-4, and one to PIRADS-5. Multivariate logistic regression analysis revealed that a PSA increase of ≥25% during follow-up was the only predictor of mpMRI upgrade (P = 0.019, OR: 2.384). 30 out of 54 patients underwent a prostate biopsy and PCa was detected in 15 patients; 5 with ISUP grade 1, 10 with ISUP grade 2. ConclusionsAlmost half of the patients with a PIRADS-2 index lesion were upgraded to PIRADS ≥3 when evaluated with serial mpMRI when a PSA increase of ≥25% was observed during follow-up. PCa was detected in half of the patients who underwent a biopsy. Serial mpMRI can be recommended when monitoring patients with elevating PSA ≥25%, a prostate biopsy can be considered upon a mpMRI progression.